Elevated expression of the V-ATPase D2 subunit triggers increased energy metabolite levels in KrasG12D-driven cancer cells

Mutations of the Ras oncogene are frequently detected in human cancers. Among Ras-mediated tumorigenesis, Kras-driven cancers are the most dominant mutation types. Here, we investigated molecular markers related to the Kras mutation, which is involved in energy metabolism in Kras mutant-driven cancer. We first generated a knock-in Kras^G12D cell line as a model. The genotype and phenotype of the Kras ^G12D-driven cells were first confirmed. Dramatically elevated metabolite characterization was observed in Kras ^G12D-driven cells compared with wild-type cells. Analysis of mitochondrial metabolite-related genes showed that two of the 84 genes in Kras ^G12D-driven cells differed from control cells by at least twofold. The messenger RNA and protein levels of ATP6V0D2 were significantly upregulated in Kras ^G12D-driven cells. Knockdown of ATP6V0D2 expression inhibited motility and invasion but did not affect the proliferation of Kras ^G12D-driven cells. We further investigated ATP6V0D2 expression in tumor tissue microarrays. ATP6V0D2 overexpression was observed in most carcinoma tissues, such as melanoma, pancreas, and kidney. Thus, we suggest that ATP6V0D2, as one of the V-ATPase (vacuolar-type H ⁺-ATPase) subunit isoforms, may be a potential therapeutic target for Kras mutation cancer.     

Molecular markers for gastric adenocarcinoma: an update

Gastric cancer is the second most common cancer worldwide. Treatment of localized gastric cancer relies primarily on surgical intervention, although growing evidence suggests that the addition of chemoradiation may improve disease-free intervals and overall survival. In this regard, the current high rates of recurrence and subsequent poor survival have prompted an ever-increasing use of multimodal strategies, even for early-stage disease. However, these therapies are often limited by debilitating toxicities and varying degrees of response efficacy. As a result, pharmacogenomics, the study of specific genetic and molecular signatures that may be predictive of treatment outcomes, has gained considerable interest. For example, studies have demonstrated that the expression of enzymes involved in the metabolism or conjugation of commonly used chemotherapy agents, such as fluoropyrimidines and cisplatin, can serve as surrogate markers predictive of chemotherapy response. Polymorphisms in the genes encoding these enzymes have also been identified and may further account for altered expression patterns, resulting in varied clinical responses. Future work is necessary to further refine the list of molecular genetic markers and to identify novel markers for prognostic and predictive purposes. Technologies such as microarray analysis may be useful in identifying new molecular genetic markers, and further work may determine whether these markers can be employed to help stratify patients into different multimodal treatment regimens.     

Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study

Although prognostic gene expression signatures for survival in early-stage lung cancer have been proposed, for clinical application, it is critical to establish their performance across different subject populations and in different laboratories. Here we report a large, training-testing, multi-site, blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) could be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early-stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas.     

Establishment and experimental validation of an immune miRNA signature for assessing prognosis and immune landscape of patients with colorectal cancer

As essential regulators of gene expression, miRNAs are engaged in the initiation and progression of colorectal cancer (CRC), including antitumour immune response. In this study, we proposed an integrated algorithm, ImmuMiRNA, for identifying miRNA modulators of immune-associated pathways. Based on these immune-associated miRNAs, we applied the LASSO algorithm to develop a reliable and individualized signature for evaluating overall survival (OS) and inflammatory landscape of CRC patients. An external public data set and qRT-PCR data from 40 samples were further utilized to validate this signature. As a result, an immune-associated miRNA prognostic signature (IAMIPS) consisting of three miRNAs (miR-194-3P, miR-216a-5p and miR-3677-3p) was established and validated. Patients in the high-risk group possessed worse OS. After stratification for clinical factors, the signature remained a powerful independent predictor for OS. IAMIPS displayed much better accuracy than the traditional clinical stage in assessing the prognosis of CRC. Further analysis revealed that patients in the high-risk group were characterized by inflammatory response, abundance immune cell infiltration, and higher immune checkpoint profiles and tumour mutation burden (TMB). In conclusion, the IAMIPS is highly predictive of OS in patients with CRC, which may serve as a powerful prognostic tool to further optimize immunotherapies for cancer.     

Integration of estrogen and progesterone receptors with pathological and molecular prognostic factors in breast cancer patients

In this study we have examined biopsies from women with localized primary breast cancer to investigate the prognostic performance of estrogen receptors (ER) and progesterone receptors (PR) for estimating the metastatic probability of the patients, and to explore whether discrimination gets better by combining clinicopathological and other molecular parameters into a score. This prospective study involved 205 patients with a median follow-up of 5 y. Among the evaluated clinicopathological data were: patient's age; tumor size; axillary lymph node involvement; and tumor grade. The most representative tumor samples were derived to a single laboratory for immunohistochemical evaluation of the following molecular markers: ER, PR, proliferating cell nuclear antigen (PCNA), p53 protein product, erbB-2 (HER-2/neu) oncoprotein, and P170 glycoprotein (mdr1 gen product). Distant metastases (study endpoint) appeared in 19.5% (40/205) of the patients, most of these patients presented a mixture of poor, regular and good prognostic factors. Disease-free survival analysis procedures (Kaplan–Meier method) identified tumor size, axillary lymph node involvement, tumor grade, receptor status, PCNA, p53, erbB-2 and P170 as useful prognostic factors. Proportional hazard regression analysis (Cox) identified in order of importance erbB-2, tumor size, receptors status, tumor grade and PCNA as useful prognostic factors. To facilitate the evaluation of the prognostic factors, a practical and simple score system was derived. A high pathological score identified 65% of the patients that developed distant metastases, while a high molecular score was obtained in 57% of patients with metastatic disease. There was a significant improvement in the diagnosis of probability of being with distant metastases when the pathological score was combined with the molecular score, 82% of the patients with distant metastases showed an elevated combined score. Validation of this scoring system will need further larger studies (validation set as opposed to the training set used in the present study). Due to the complexity of events in cancer, the evaluation of a combination of prognostic factors should be of value to clinicians to make a more objective estimate of the prognosis of individual breast cancer patients.     

Kras Gene Mutation and RASSF1A,FHIT and MGMT Gene Promoter Hypermethylation: Indicators of Tumor Staging and Metastasis in Adenocarcinomatous Sporadic Colorectal Cancer in Indian Population

Objective

Colorectal cancer (CRC) development involves underlying modifications at genetic/epigenetic level. This study evaluated the role of Kras gene mutation and RASSF1A, FHIT and MGMT gene promoter hypermethylation together/independently in sporadic CRC in Indian population and correlation with clinicopathological variables of the disease.

Methods

One hundred and twenty four consecutive surgically resected tissues (62 tumor and equal number of normal adjacent controls) of primary sporadic CRC were included and patient details including demographic characteristics, lifestyle/food or drinking habits, clinical and histopathological profiles were recorded. Polymerase chain reaction - Restriction fragment length polymorphism and direct sequencing for Kras gene mutation and Methylation Specific-PCR for RASSF1A, FHIT and MGMT genes was performed.

Results

Kras gene mutation at codon 12 & 13 and methylated RASSF1A, FHIT and MGMT gene was observed in 47%, 19%, 47%, 37% and 47% cases, respectively. Alcohol intake and smoking were significantly associated with presence of Kras mutation (codon 12) and MGMT methylation (p-value <0.049). Tumor stage and metastasis correlated with presence of mutant Kras codon 12 (p-values 0.018, 0.044) and methylated RASSF1A (p-values 0.034, 0.044), FHIT (p-values 0.001, 0.047) and MGMT (p-values 0.018, 0.044) genes. Combinatorial effect of gene mutation/methylation was also observed (p-value <0.025). Overall, tumor stage 3, moderately differentiated tumors, presence of lymphatic invasion and absence of metastasis was more frequently observed in tumors with mutated Kras and/or methylated RASSF1A, FHIT and MGMT genes.

Conclusion

Synergistic interrelationship between these genes in sporadic CRC may be used as diagnostic/prognostic markers in assessing the overall pathological status of CRC.     

Noninvasive Image Texture Analysis Differentiates K-ras Mutation from Pan-Wildtype NSCLC and Is Prognostic

Background

Non-invasive characterization of a tumor''s molecular features could enhance treatment management. Quantitative computed tomography (CT) based texture analysis (QTA) has been used to derive tumor heterogeneity information, and the appearance of the tumors has been shown to relate to patient outcome in non-small cell lung cancer (NSCLC) and other cancers. In this study, we examined the potential of tumoral QTA to differentiate K-ras mutant from pan-wildtype tumors and its prognostic potential using baseline pre-treatment non-contrast CT imaging in NSCLC.

Methods

Tumor DNA from patients with early-stage NSCLC was analyzed on the LungCarta Panel. Cases with a K-ras mutation or pan-wildtype for 26 oncogenes and tumor suppressor genes were selected for QTA. QTA was applied to regions of interest in the primary tumor. Non-parametric Mann Whitney test assessed the ability of the QTA, clinical and patient characteristics to differentiate between K-ras mutation from pan-wildtype. A recursive decision tree was developed to determine whether the differentiation of K-ras mutant from pan-wildtype tumors could be improved by sequential application of QTA parameters. Kaplan-Meier survival analysis assessed the ability of these markers to predict survival.

Results

QTA was applied to 48 cases identified, 27 had a K-ras mutation and 21 cases were pan-wildtype. Positive skewness and lower kurtosis were significantly associated with the presence of a K-ras mutation. A five node decision tree had sensitivity, specificity, and accuracy values (95% CI) of 96.3% (78.1–100), 81.0% (50.5–97.4), and 89.6% (72.9–97.0); respectively. Kurtosis was a significant predictor of OS and DFS, with a lower kurtosis value linked with poorer survival.

Conclusions

Lower kurtosis and positive skewness are significantly associated with K-ras mutations. A QTA feature such as kurtosis is prognostic for OS and DFS. Non-invasive QTA can differentiate the presence of K-ras mutation from pan-wildtype NSCLC and is associated with patient survival.     

Prostate cancer: epidemiology, screening, and biomarkers

Carcinoma of the prostate continues to be a major health problem in the United States. Beginning in 1988, a marked increase in detection of prostate cancer occurred due to the development of a test for prostate-specific antigen (PSA). Controversy exists, however, about the value of PSA as a tumor marker. Although it has prognostic significance both before and after definitive therapy for prostate cancer, it is unclear whether routine PSA screening will translate into a survival advantage for patients. Because of its limitations, PSA may not ultimately be a good enough marker to be used as a screening tool. However, molecular biology has led to a rapid rise in the number of potential new prostate tumor markers, which may eventually overcome the weaknesses of PSA. Considerable progress has occurred in the diagnosis and management of prostate cancer: more is understood about the risk factors for the disease, possible ways to prevent it, and new ways to diagnose and monitor it. These developments have already translated into better patient care, while also identifying where further improvements are needed.     

Kernel machine approach to testing the significance of multiple genetic markers for risk prediction

There is growing evidence that genomic and proteomic research holds great potential for changing irrevocably the practice of medicine. The ability to identify important genomic and biological markers for risk assessment can have a great impact in public health from disease prevention, to detection, to treatment selection. However, the potentially large number of markers and the complexity in the relationship between the markers and the outcome of interest impose a grand challenge in developing accurate risk prediction models. The standard approach to identifying important markers often assesses the marginal effects of individual markers on a phenotype of interest. When multiple markers relate to the phenotype simultaneously via a complex structure, such a type of marginal analysis may not be effective. To overcome such difficulties, we employ a kernel machine Cox regression framework and propose an efficient score test to assess the overall effect of a set of markers, such as genes within a pathway or a network, on survival outcomes. The proposed test has the advantage of capturing the potentially nonlinear effects without explicitly specifying a particular nonlinear functional form. To approximate the null distribution of the score statistic, we propose a simple resampling procedure that can be easily implemented in practice. Numerical studies suggest that the test performs well with respect to both empirical size and power even when the number of variables in a gene set is not small compared to the sample size.     

非小细胞肺癌靶向治疗的临床前研究进展

针对表皮生长因子受体（EGFR）和血管生成（angiogenesis）信号通路的靶向治疗已经在晚期非小细胞肺癌的治疗上取得成功,但由于抗药性的存在,大多数晚期患者的生存时间仍然提高有限。继发性的EGFR T790M突变和原癌基因肝细胞生长因子受体（MET）的扩增被鉴定为两种主要的抗药机制。最近转化生长因子-β（TGF-β）/白介素-6信号通路被报道能介导选择性和适应性地对erlotinib的抗药。另一方面,Kras突变所致肺癌的靶向治疗方面也取得了一些进展。双重抑制磷脂酰肌醇3-激酶（PI3K）和促分裂素原活化蛋白激酶激酶（MEK）信号通路可导致Kras突变肿瘤的显著消退,联合抑制SRC、PI3K和MEK可使丝氨酸/苏氨酸蛋白激酶11（Lkb1）缺失,Kras突变的肺癌小鼠的肿瘤明显消退,抑制核因子-κB（NF-κB）信号通路导致p53缺失,Kras突变的肿瘤发展显著减慢。这些发现都为发展非小细胞肺癌患者的靶向治疗提供了有力的支持。     

Identifying gene expression changes in breast cancer that distinguish early and late relapse among uncured patients

MOTIVATION: In recent years, microarray technology has revealed many tumor-expressed genes prognostic of clinical outcomes in early-stage breast cancer patients. However, in the presence of cured patients, evaluating gene effect on time to relapse is quite complex since it may affect either the probability of never experiencing a relapse (cure effect) or the time to relapse among the uncured patients (disease progression effect) or both. In this context, we propose a simple and an efficient method for identifying gene expression changes that characterize early and late recurrence for uncured patients. RESULTS: Simulation results show the good performance of the proposed statistic for detecting a disease progression effect. In a study of early-stage breast cancer, our results show that the proposed statistic provides a more powerful basis for gene selection than the classical Cox model-based statistic. From a biological perspective, many of the genes identified here as associated with the speed of disease recurrence have known roles in tumorigenesis.     

Prognostic factors in prostate cancer

Prognostic factors in organ confined prostate cancer will reflect survival after surgical radical prostatectomy. Gleason score, tumour volume, surgical margins and Ki-67 index have the most significant prognosticators. Also the origins from the transitional zone, p53 status in cancer tissue, stage, and aneuploidy have shown prognostic significance. Progression-associated features include Gleason score, stage, and capsular invasion, but PSA is also highly significant. Progression can also be predicted with biological markers (E-cadherin, microvessel density, and aneuploidy) with high level of significance. Other prognostic features of clinical or PSA-associated progression include age, IGF-1, p27, and Ki-67. In patients who were treated with radiotherapy the survival was potentially predictable with age, race and p53, but available research on other markers is limited. The most significant published survival-associated prognosticators of prostate cancer with extension outside prostate are microvessel density and total blood PSA. However, survival can potentially be predicted by other markers like androgen receptor, and Ki-67-positive cell fraction. In advanced prostate cancer nuclear morphometry and Gleason score are the most highly significant progression-associated prognosticators. In conclusion, Gleason score, capsular invasion, blood PSA, stage, and aneuploidy are the best markers of progression in organ confined disease. Other biological markers are less important. In advanced disease Gleason score and nuclear morphometry can be used as predictors of progression. Compound prognostic factors based on combinations of single prognosticators, or on gene expression profiles (tested by DNA arrays) are promising, but clinically relevant data is still lacking.     

DNA Methylation Patterns Can Estimate Nonequivalent Outcomes of Breast Cancer with the Same Receptor Subtypes

Breast cancer has various molecular subtypes and displays high heterogeneity. Aberrant DNA methylation is involved in tumor origin, development and progression. Moreover, distinct DNA methylation patterns are associated with specific breast cancer subtypes. We explored DNA methylation patterns in association with gene expression to assess their impact on the prognosis of breast cancer based on Infinium 450K arrays (training set) from The Cancer Genome Atlas (TCGA). The DNA methylation patterns of 12 featured genes that had a high correlation with gene expression were identified through univariate and multivariable Cox proportional hazards models and used to define the methylation risk score (MRS). An improved ability to distinguish the power of the DNA methylation pattern from the 12 featured genes (p = 0.00103) was observed compared with the average methylation levels (p = 0.956) or gene expression (p = 0.909). Furthermore, MRS provided a good prognostic value for breast cancers even when the patients had the same receptor status. We found that ER-, PR- or Her2- samples with high-MRS had the worst 5-year survival rate and overall survival time. An independent test set including 28 patients with death as an outcome was used to test the validity of the MRS of the 12 featured genes; this analysis obtained a prognostic value equivalent to the training set. The predict power was validated through two independent datasets from the GEO database. The DNA methylation pattern is a powerful predictor of breast cancer survival, and can predict outcomes of the same breast cancer molecular subtypes.     

Estimating cancer survival and clinical outcome based on genetic tumor progression scores

MOTIVATION: In cancer research, prediction of time to death or relapse is important for a meaningful tumor classification and selecting appropriate therapies. Survival prognosis is typically based on clinical and histological parameters. There is increasing interest in identifying genetic markers that better capture the status of a tumor in order to improve on existing predictions. The accumulation of genetic alterations during tumor progression can be used for the assessment of the genetic status of the tumor. For modeling dependences between the genetic events, evolutionary tree models have been applied. RESULTS: Mixture models of oncogenetic trees provide a probabilistic framework for the estimation of typical pathogenetic routes. From these models we derive a genetic progression score (GPS) that estimates the genetic status of a tumor. GPS is calculated for glioblastoma patients from loss of heterozygosity measurements and for prostate cancer patients from comparative genomic hybridization measurements. Cox proportional hazard models are then fitted to observed survival times of glioblastoma patients and to times until PSA relapse following radical prostatectomy of prostate cancer patients. It turns out that the genetically defined GPS is predictive even after adjustment for classical clinical markers and thus can be considered a medically relevant prognostic factor. AVAILABILITY: Mtreemix, a software package for estimating tree mixture models, is freely available for non-commercial users at http://mtreemix.bioinf.mpi-sb.mpg.de. The raw cancer datasets and R code for the analysis with Cox models are available upon request from the corresponding author.     

应用结直肠癌基因检测指导术后化疗

为了探讨结直肠癌基因检测在术后化疗中的应用价值,本研究于2015年2月至2017年2月期间,选取在我院行结直肠癌根治术患者102例,根据患者选取的治疗方案,分为观察组(n=47)和对照组(n=55)。其中观察组根据术后肿瘤组织基因检测结果给予化疗方案,对照组直接选用FOLFOX4方案,随访观察两组无进展生存期和总生存期。研究发现,观察组检测到1例Nras基因突变,3例Braf基因突变,19例Kras基因突变,2例Pik3ca基因突变;Kras基因突变与肿瘤部位和分化程度有关(p<0.05);观察组中位无进展生存期为23个月,明显长于对照组的17个月,差异比较具有统计学意义(p<0.05);观察组中位总生存期为31个月,明显长于对照组的25个月,差异比较具有统计学意义(p<0.05);观察组和对照组Ⅲ～Ⅳ级肝肾损害、骨髓抑制和胃肠道反应比例比较差异无统计学意义(p>0.05)。研究表明结直肠癌基因检测指导术后化疗,可以提高患者无进展生存期和总生存期,具有较好的应用价值。     

Protein kinase Cι expression and oncogenic signaling mechanisms in cancer

Accumulating evidence demonstrates that PKCι is an oncogene and prognostic marker that is frequently targeted for genetic alteration in many major forms of human cancer. Functional data demonstrate that PKCι is required for the transformed phenotype of lung, pancreatic, ovarian, prostate, colon, and brain cancer cells. Future studies will be required to determine whether PKCι is also an oncogene in the many other cancer types that also overexpress PKCι. Studies of PKCι using genetically defined models of tumorigenesis have revealed a critical role for PKCι in multiple stages of tumorigenesis, including tumor initiation, progression, and metastasis. Recent studies in a genetic model of lung adenocarcinoma suggest a role for PKCι in transformation of lung cancer stem cells. These studies have important implications for the therapeutic use of aurothiomalate (ATM), a highly selective PKCι signaling inhibitor currently undergoing clinical evaluation. Significant progress has been made in determining the molecular mechanisms by which PKCι drives the transformed phenotype, particularly the central role played by the oncogenic PKCι-Par6 complex in transformed growth and invasion, and of several PKCι-dependent survival pathways in chemo-resistance. Future studies will be required to determine the composition and dynamics of the PKCι-Par6 complex, and the mechanisms by which oncogenic signaling through this complex is regulated. Likewise, a better understanding of the critical downstream effectors of PKCι in various human tumor types holds promise for identifying novel prognostic and surrogate markers of oncogenic PKCι activity that may be clinically useful in ongoing clinical trials of ATM.     

Ion Channel Gene Expression in Lung Adenocarcinoma: Potential Role in Prognosis and Diagnosis

Ion channels are known to regulate cancer processes at all stages. The roles of ion channels in cancer pathology are extremely diverse. We systematically analyzed the expression patterns of ion channel genes in lung adenocarcinoma. First, we compared the expression of ion channel genes between normal and tumor tissues in patients with lung adenocarcinoma. Thirty-seven ion channel genes were identified as being differentially expressed between the two groups. Next, we investigated the prognostic power of ion channel genes in lung adenocarcinoma. We assigned a risk score to each lung adenocarcinoma patient based on the expression of the differentially expressed ion channel genes. We demonstrated that the risk score effectively predicted overall survival and recurrence-free survival in lung adenocarcinoma. We also found that the risk scores for ever-smokers were higher than those for never-smokers. Multivariate analysis indicated that the risk score was a significant prognostic factor for survival, which is independent of patient age, gender, stage, smoking history, Myc level, and EGFR/KRAS/ALK gene mutation status. Finally, we investigated the difference in ion channel gene expression between the two major subtypes of non-small cell lung cancer: adenocarcinoma and squamous-cell carcinoma. Thirty ion channel genes were identified as being differentially expressed between the two groups. We suggest that ion channel gene expression can be used to improve the subtype classification in non-small cell lung cancer at the molecular level. The findings in this study have been validated in several independent lung cancer cohorts.     

Ferroptosis-related gene signature correlates with the tumor immune features and predicts the prognosis of glioma patients

Background: Glioma is a malignant intracranial tumor and the most fatal cancer. The role of ferroptosis in the clinical progression of gliomas is unclear.Method: Univariate and least absolute shrinkage and selection operator (Lasso) Cox regression methods were used to develop a ferroptosis-related signature (FRSig) using a cohort of glioma patients from the Chinese Glioma Genome Atlas (CGGA), and was validated using an independent cohort of glioma patients from The Cancer Genome Atlas (TCGA). A single-sample gene set enrichment analysis (ssGSEA) was used to calculate levels of the immune infiltration. Multivariate Cox regression was used to determine the independent prognostic role of clinicopathological factors and to establish a nomogram model for clinical application.Results: We analyzed the correlations between the clinicopathological features and ferroptosis-related gene (FRG) expression and established an FRSig to calculate the risk score for individual glioma patients. Patients were stratified into two subgroups with distinct clinical outcomes. Immune cell infiltration in the glioma microenvironment and immune-related indexes were identified that significantly correlated with the FRSig, the tumor mutation burden (TMB), copy number alteration (CNA), and immune checkpoint expression was also significantly positively correlated with the FRSig score. Ultimately, an FRSig-based nomogram model was constructed using the independent prognostic factors age, World Health Organization (WHO) grade, and FRSig score.Conclusion: We established the FRSig to assess the prognosis of glioma patients. The FRSig also represented the glioma microenvironment status. Our FRSig will contribute to improve patient management and individualized therapy by offering a molecular biomarker signature for precise treatment.     

Proteomics in prostate cancer research

The incidence of early prostate cancer (PCa) among middle-aged men has increased rapidly. For many of these men, curatively intended treatment does more harm than good. Established prognostic factors are tumor stage and grade. As a result of earlier detection a majority of patients now have nonpalpable tumors (T1c) of intermediate grade (Gleason score 6). Prostate specific antigen in serum in such cases is generally at a low level and not a reliable predictor of prognosis. Altogether there is an urgent need for adjunctive prognostic indicators. In the search for relevant tumor markers for improved patient selection an exploration of the proteome (the human proteins) could be fruitful. This paper critically reviews the use of 2-dimensional gel electrophoresis (2-DE) for proteome research. Additional steps such as image analysis and mass spectrometry are described. Techniques based on non-2-DE platforms: surface-enhanced laser desorption/ionization (SELDI), isotope coded affinity tags (ICAT) and array-based technologies are also summarized. Although labor-intensive and time-consuming, 2-DE is presently the most powerful method for analysis of cellular protein phenotype and may potentially reveal gene regulations that cannot be detected on a genetic level.